dalibo/pg_activity

pg_activity is a top like application for PostgreSQL server activity monitoring.

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dalibo/pg_activity has 3k+ stars and 200+ forks on GitHub, is written in Python, and was last pushed on Sep 21, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 2 hours ago
Added to GitGenius on September 22nd, 2026
Created on October 28th, 2012
Open Issues & Pull Requests: 18 (+0)
GitHub issues: Enabled
Number of forks: 204
Total Stargazers: 3,053 (+0)
Total Subscribers: 45 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 12.6 hours
Mean response time: 12.8 days
90th percentile: 21.9 days
Tracked items: 19

Maintainer activity

1 person did triage or write work on this repository in the last 12 months.

Counts unlabeled, assigned, unassigned, milestoned, demilestoned, locked, unlocked over the last 12 months. These are issue and pull request events that require triage or write permission. Commits and code review are not counted. labeled and renamed are excluded because GitHub issue forms record the issue author as the actor. Figures from October 18, 2026. This count is not comparable across projects: each project's automation decides which of these events a person emits. How this is counted.

Charts & Analytics

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Issue Activity (beta)

Open issues: 10
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 810 days
Stale 30+ days: 10
Stale 90+ days: 9

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (10)
  • bug (5)
  • documentation (1)
  • packaging (1)

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Detailed Description

pg_activity is a command-line monitoring tool for PostgreSQL server activity that works like the Unix top utility.

The tool addresses the need to observe what is happening on a PostgreSQL server in real time. It displays active queries, connections, and system-level information in an interactive terminal interface, allowing database administrators and developers to identify slow queries, connection bottlenecks, and resource contention without writing custom monitoring queries or setting up separate infrastructure.

The tool suits anyone managing PostgreSQL servers who needs quick visibility into database activity from the command line. It works both locally and remotely, though local execution with the postgres system user or root provides the most complete information including system metrics and temporary file data. Users without superuser privileges can still run the tool in a degraded mode that omits some system-level details. Installation is straightforward through distribution package managers on Debian and RPM-based systems, through PyPI with pip or pipx, or from source for testing development versions.

Development activity shows consistent engagement with the codebase through regular commits addressing bugs and feature requests. The project maintains responsiveness to user-reported issues and incorporates feedback into updates. Documentation is actively maintained to reflect current functionality and installation methods across multiple platforms. The maintainers provide clear guidance on version compatibility and direct users to appropriate channels for packaging-related problems rather than treating distribution issues as project bugs.